Development and validation of a prognostic model based on immune variables to early predict severe cases of SARS-CoV-2 Omicron variant infection

Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant has prevailed globally since November 2021. The extremely high transmissibility and occult manifestations were notable, but the severity and mortality associated with the Omicron variant and subvariants cannot be ignored, especially for immunocompromised populations. However, no prognostic model for specially predicting the severity of the Omicron variant infection is available yet. In this study, we aim to develop and validate a prognostic model based on immune variables to early recognize potentially severe cases of Omicron variant-infected patients. Methods This was a single-center prognostic study involving patients with SARS-CoV-2 Omicron variant infection. Eligible patients were randomly divided into the training and validation cohorts. Variables were collected immediately after admission. Candidate variables were selected by three variable-selecting methods and were used to construct Cox regression as the prognostic model. Discrimination, calibration, and net benefit of the model were evaluated in both training and validation cohorts. Results Six hundred eighty-nine of the involved 2,645 patients were eligible, consisting of 630 non-ICU cases and 59 ICU cases. Six predictors were finally selected to establish the prognostic model: age, neutrophils, lymphocytes, procalcitonin, IL-2, and IL-10. For discrimination, concordance indexes in the training and validation cohorts were 0.822 (95% CI: 0.748-0.896) and 0.853 (95% CI: 0.769-0.942). For calibration, predicted probabilities and observed proportions displayed high agreements. In the 21-day decision curve analysis, the threshold probability ranges with positive net benefit were 0~1 and nearly 0~0.75 in the training and validation cohorts, correspondingly. Conclusions This model had satisfactory high discrimination, calibration, and net benefit. It can be used to early recognize potentially severe cases of Omicron variant-infected patients so that they can be treated timely and rationally to reduce the severity and mortality of Omicron variant infection.

SARS-CoV-2 Omicron XBB subvariants exhibit enhanced fusogenicity and substantial immune evasion in elderly population, but high sensitivity to pan-coronavirus fusion inhibitors.

Numerous emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariants have shown significant immune evasion capacity and caused a large number of infections, as well as vaccine-breakthrough infections, especially in elderly populations. Recently emerged Omicron XBB was derived from the BA.2 lineage, but bears a distinct mutant profile in its spike (S) protein. In this study, we found that Omicron XBB S protein drove more efficient membrane-fusion kinetics on human lung-derived cells (Calu-3). Considering the high susceptibility of the elderly to the current Omicron pandemic, we performed a comprehensive neutralization assessment of elderly convalescent or vaccine sera against XBB infection. We found that the sera from elderly convalescent patients who experienced with BA.2 infection or breakthrough infection potently inhibited BA.2 infection, but showed significantly reduced efficacy against XBB. Moreover, recently emerged XBB.1.5 subvariant also showed more significant resistance to the convalescent sera of BA.2- or BA.5-infected elderly. On the other hand, we found that the pan-CoV fusion inhibitors EK1 and EK1C4 can potently block either XBB-S- or XBB.1.5-S-mediated fusion process and viral entry. Moreover, EK1 fusion inhibitor showed potent synergism when combined with convalescent sera of BA.2- or BA.5-infected patients against XBB and XBB.1.5 infection, further indicating that EK1-based pan-CoV fusion inhibitors are promising candidates for development as clinical antiviral agents to combat the Omicron XBB subvariants.

Development and validation of a prognostic model based on immune variables to early predict severe cases of SARS-CoV-2 Omicron variant infection.

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant has prevailed globally since November 2021. The extremely high transmissibility and occult manifestations were notable, but the severity and mortality associated with the Omicron variant and subvariants cannot be ignored, especially for immunocompromised populations. However, no prognostic model for specially predicting the severity of the Omicron variant infection is available yet. In this study, we aim to develop and validate a prognostic model based on immune variables to early recognize potentially severe cases of Omicron variant-infected patients. Methods: This was a single-center prognostic study involving patients with SARS-CoV-2 Omicron variant infection. Eligible patients were randomly divided into the training and validation cohorts. Variables were collected immediately after admission. Candidate variables were selected by three variable-selecting methods and were used to construct Cox regression as the prognostic model. Discrimination, calibration, and net benefit of the model were evaluated in both training and validation cohorts. Results: Six hundred eighty-nine of the involved 2,645 patients were eligible, consisting of 630 non-ICU cases and 59 ICU cases. Six predictors were finally selected to establish the prognostic model: age, neutrophils, lymphocytes, procalcitonin, IL-2, and IL-10. For discrimination, concordance indexes in the training and validation cohorts were 0.822 (95% CI: 0.748-0.896) and 0.853 (95% CI: 0.769-0.942). For calibration, predicted probabilities and observed proportions displayed high agreements. In the 21-day decision curve analysis, the threshold probability ranges with positive net benefit were 0~1 and nearly 0~0.75 in the training and validation cohorts, correspondingly. Conclusions: This model had satisfactory high discrimination, calibration, and net benefit. It can be used to early recognize potentially severe cases of Omicron variant-infected patients so that they can be treated timely and rationally to reduce the severity and mortality of Omicron variant infection.

Alterations in smell or taste in individuals infected with SARS-CoV-2 during periods of Omicron variant dominance.

OBJECTIVES: To characterize the prevalence, severity, correlation with initial symptoms, and role of vaccination in patients with COVID-19 with smell or taste alterations (STAs). METHODS: We conducted an observational study of patients infected with SARS-CoV-2 Omicron admitted to three hospitals between May 17 and June 16, 2022. The olfactory and gustatory functions were evaluated using the taste and smell survey and the numerical visual analog scale at two time points. RESULTS: The T1 and T2 time point assessments were completed by 688 and 385 participants, respectively. The prevalence of STAs at two time points was 41.3% vs 42.6%. Furthermore, no difference existed in the severity distribution of taste and smell survey, smell, or taste visual analog scale scores between the groups. Patients with initial symptoms of headache (P = 0.03) and muscle pain (P = 0.04) were more likely to develop STAs, whereas higher education; three-dose vaccination; no symptoms yet; or initial symptoms of cough, throat discomfort, and fever demonstrated protective effects, and the results were statistically significant. CONCLUSION: The prevalence of STAs did not decrease significantly during the Omicron dominance, but the severity was reduced, and vaccination demonstrated a protective effect. In addition, the findings suggest that the presence of STAs is likely to be an important indicator of viral invasion of the nervous system.

The derived neutrophil to lymphocyte ratio can be the predictor of prognosis for COVID-19 Omicron BA.2 infected patients.

Background: Several systemic inflammatory biomarkers have been associated with poor overall survival (OS) and disease severity in patients with coronavirus disease 2019 (COVID-19). However, it remains unclear which markers are better for predicting prognosis, especially for COVID-19 Omicron BA.2 infected patients. The present study aimed to identify reliable predictors of prognosis of COVID-19 Omicron BA.2 from inflammatory indicators. Methods: A cohort of 2645 COVID-19 Omicron BA.2 infected patients were retrospectively analyzed during the Omicron BA.2 surge in Shanghai between April 12, 2022, and June 17, 2022. The patients were admitted to the Shanghai Fourth People's Hospital, School of Medicine, Tongji University. Six systemic inflammatory indicators were included, and their cut-off points were calculated using maximally selected rank statistics. The analysis involved Kaplan-Meier curves, univariate and multivariate Cox proportional hazard models, and time-dependent receiver operating characteristic curves (time-ROC) for OS-associated inflammatory indicators. Results: A total of 2347 COVID-19 Omicron BA.2 infected patients were included. All selected indicators proved to be independent predictors of OS in the multivariate analysis (all P < 0.01). A high derived neutrophil to lymphocyte ratio (dNLR) was associated with a higher mortality risk of COVID-19 [hazard ratio, 4.272; 95% confidence interval (CI), 2.417-7.552]. The analyses of time-AUC and C-index showed that the dNLR (C-index: 0.844, 0.824, and 0.718 for the 5th, 10th, and 15th day, respectively) had the best predictive power for OS in COVID-19 Omicron BA.2 infected patients. Among different sub-groups, the dNLR was the best predictor for OS regardless of age (0.811 for patients aged ≥70 years), gender (C-index, 0.880 for men and 0.793 for women) and disease severity (C-index, 0.932 for non-severe patients and 0.658 for severe patients). However, the platelet to lymphocyte ratio was superior to the other indicators in patients aged <70 years. Conclusions: The prognostic ability of the dNLR was higher than the other evaluated inflammatory indicators for all COVID-19 Omicron BA.2 infected patients.

Intubation and Ventilation amid the COVID-19 Outbreak: Wuhan's Experience.

The COVID-19 outbreak has led to 80,409 diagnosed cases and 3,012 deaths in mainland China based on the data released on March 4, 2020. Approximately 3.2% of patients with COVID-19 required intubation and invasive ventilation at some point in the disease course. Providing best practices regarding intubation and ventilation for an overwhelming number of patients with COVID-19 amid an enhanced risk of cross-infection is a daunting undertaking. The authors presented the experience of caring for the critically ill patients with COVID-19 in Wuhan. It is extremely important to follow strict self-protection precautions. Timely, but not premature, intubation is crucial to counter a progressively enlarging oxygen debt despite high-flow oxygen therapy and bilevel positive airway pressure ventilation. Thorough preparation, satisfactory preoxygenation, modified rapid sequence induction, and rapid intubation using a video laryngoscope are widely used intubation strategies in Wuhan. Lung-protective ventilation, prone position ventilation, and adequate sedation and analgesia are essential components of ventilation management.